Principles and Practice of Pharmaceutical Medicine

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It will provide a much more robust basis than
presently possible for simulations of phase III
clinical trials, because they will be based on
actual rather than assumed dosing histories
and on oversimplified pharmacodynamic
characterizations.

27.7 During drug development
(phase III studies)

A pharmionic program can be implemented to
enhance patient adherence, based on the princi-
ple that ‘what is measured can be managed;
what wasn’t measured didn’t happen’. In a con-
firmatory trial, it is crucial to guarantee that
patients get the optimal exposure to the test
drug.


In placebo-controlled studies, this approach
will guarantee a greatest average improve-
ment in the response of the test drug compared
to the placebo effect.

In positive-controlled studies, the assurance of
good exposure to the test drugs is essential for
maximal assay sensitivity, to guarantee that
the claim of equivalence is not related to a lack
of drug exposure.

Having reliable pharmionic data avoids the
increase in variance of the response that arises
from variable execution of the prescribed dos-
ing regimen – widely recognized as a leading
source of variance in drug response. In engi-
neering terms, having reliable pharmionic
data converts ‘noise’ into ‘signal’.

The implementation of such a program could
thus result in an increase of study power or
equivalently in a smaller sample size needed
to achieve a given level of statistical power,
resulting in a shorter and less expensive con-
firmatory phase.

Supportive pharmionic analysis in addition to
conventional intention-to-treat (ITT) analysis.


As another supplement to the ITT analysis,
a pharmionic program will allow robust
estimates of:

the treatment response that can be expected
within the subpopulation of patients who dose
essentially correctly, as estimated by current
methods of causal inference;

dosing errors that have the greatest potential to
undermine effectiveness;

dosing errors that have the greatest potential to
create hazard (e.g. rebound effects after sud-
den cessation of dosing, recurrent first-dose
effects, emergence of resistance to anti-infec-
tive agents and the like).

Against the background of firm knowledge of
the impact of particular patterns of on–off–on
dosing, the full benefit of the drug can thus be
estimated and be used as supportive data.

Confirmatory studies that could fail due to the
usual patterns and prevalence of non-adherence
to prescribed therapy could instead succeed
through a pharmionics-based supportive pro-
gram bringing adequate statistical power for a
successful phase III program.

In conclusion, the economic advantages of faster
product development and earlier termination of
inherently weak product candidates (Urquhart
and Chevalley, 1988; Urquhart, 2001) are well
understood. So are the economics of bringing
products of superior therapeutic power to the
marketplace. The expression of these basic
facts in specific programs of drug development
are frequently obscured or confounded by the
biggest single source of variance in drug
response, which is unmeasured but highly vari-
able compliance of ambulatory patients with
protocol-specified drug regimens. Historically,
variable patient compliance has had vague
recognition, mainly because the then-available
methods for quantifying drug exposure in ambu-
latory patients were grossly inadequate. That
situation has changed, and it is now possible
to measure and manage patient adherence to

360 CH27 PATIENT COMPLIANCE: PHARMIONICS, A NEW DISCIPLINE

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